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Am using libsvm for image classification in matlab. What does training_label_vector exactly mean in “svmtrain” command. What does testing_label_vector and testing_instance_matrix in “svmpredict”. After training how to use the results.
For SVM, each example contains two parts: an input object (typically a vector containing the data) and a desired output value or label to specify which object/class it belongs to. Training Label vector basically represents the class the vector belongs to. For the two-class classification, the values for Training Label will be 1 or -1. So some of the features will be given a label as 1 as some as -1. This applies to Testing Label vector. Testing Instance matrix represents the data which you are trying to test the model with.
After training, the model will be outputted and you have to test with the testing matrix and testing labels to get the accuarcy of the classifier.
To read more on SVM, this is a good link: http://www.tristanfletcher.co.uk/SVM%20Explained.pdf